A fuzzy equilibrium strategy for sustainable water quality management in river-reservoir system

Presence of various stakeholders in water resources management may arise conflicts and intensify the complexity of decision making. To reduce eutrophication potential in a river-reservoir system with discharges from aquaculture industries, an equilibrium strategy-based Multi-Pollutant Waste Load Allocation (MPWLA) program is developed. Proposed MPWLA model links a surrogate to CE-QUAL-W2 water quality model, with artificial neural networks setting, with an evolutionary optimization algorithm in an adaptive surrogate-based Simulation-Optimization framework. Environmental and economic objectives are formulated as fuzzy membership functions to deal with ambiguities and imprecisions in defining the goals of study. To consider the conflicting preferences of stakeholders, (i.e., Iran Department of Environment and aquaculture units), the Stackelberg game is applied and the results are compared with those of Nash Bargaining solution. Performance of the proposed approach is illustrated by its application to Behesht-Abad River-Reservoir system, Iran. Results indicate that application of the model may reduce the eutrophication potential in the Behesht-Abad water body by offering an equilibrium strategy. Comparing two decision-making approaches (Stackelberg and Nash Bargaining) also reveals that the leader in Stackelberg, as fine and constraint setter, benefits from the premier position, leading to higher environmental penalty tariffs, less fish production capacities, and consequently better water quality rather than the Nash bargaining solution.